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Record W2890953042 · doi:10.1098/rsos.180837

Synthesis of novel ( <i>E</i> )-1-(2-(2-(4(dimethylamino) benzylidene) hydrazinyl)-4-methylthiazol-5-yl)ethanone derivatives as ecto-5′-nucleotidase inhibitors

2018· article· en· W2890953042 on OpenAlexafffund
Sidra Hassan, Pervaiz Ali Channar, Fayaz Ali Larik, Aamer Saeed, Hamid Saeed Shah, Joanna Lecka, Jean Sévigny, Jamshed Iqbal

Bibliographic record

VenueRoyal Society Open Science · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health ResearchHigher Education Commision, PakistanOrganisation for the Prohibition of Chemical Weapons
KeywordsChemistry5'-nucleotidaseEnzymeStereochemistryDocking (animal)ThiazoleBiochemistryMedicine

Abstract

fetched live from OpenAlex

Ecto-5′-nucleotidase (e5′NT), a membrane-bound enzyme and an essential member of ecto-nucleotidases which regulates extracellular purinergic signalling. Their upregulation results in various disease conditions, for example, inflammation, hypoxia and cancer. Therefore, efforts have been made to synthesize potent and selective inhibitors of e5′NT. Here we have synthesized, characterized and evaluated six thiazole derivatives (3a–3f) as potent e5′NT inhibitors. Among all derivatives, the compound ( E )-1-(4-methyl-2-(2-(pyridin-3-ylmethylene)hydrazinyl) thiazol-5-yl)ethanone (3a) exhibited maximum inhibition towards both human and rat enzymes. However, their potency against h -e5′NT was 24-fold higher than r -e5′NT. Only two compounds exhibited inhibitory behaviour towards r -e5′NT. The molecular structures of these derivatives were confirmed with the help of solid-state characterization through NMR ( 1 H and 13 C), FTIR and elemental analysis. Additionally, molecular docking was also implemented to explain putative bonding interaction between the active site of an enzyme and potent inhibitors.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.290
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2018
Admission routes2
Has abstractyes

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